diff --git a/mindspore/nn/optim/momentum.py b/mindspore/nn/optim/momentum.py
index 5ce7bd28232..7dd5ea8a5b0 100755
--- a/mindspore/nn/optim/momentum.py
+++ b/mindspore/nn/optim/momentum.py
@@ -58,13 +58,13 @@ class Momentum(Optimizer):
 
     If use_nesterov is True:
         .. math::
-            p_{t} = grad \ast lr + v_{t} \ast u \ast lr
+            p_{t} =  p_{t-1} - (grad \ast lr + v_{t} \ast u \ast lr)
 
     If use_nesterov is Flase:
         .. math::
-            p_{t} = lr \ast v_{t}
+            p_{t} = p_{t-1} - lr \ast v_{t}
 
-    Here: where grad, lr, p, v and u denote the gradients, learning_rate, parameter, accum, and momentum respectively.
+    Here: where grad, lr, p, v and u denote the gradients, learning_rate, params, moments, and momentum respectively.
 
     Args:
         params (Union[list[Parameter], list[dict]]): When the `params` is a list of `Parameter` which will be updated,
diff --git a/mindspore/nn/optim/sgd.py b/mindspore/nn/optim/sgd.py
index 406ad9f48dc..48011042151 100755
--- a/mindspore/nn/optim/sgd.py
+++ b/mindspore/nn/optim/sgd.py
@@ -57,7 +57,7 @@ class SGD(Optimizer):
         .. math::
             p_{t+1} = p_{t} - lr \ast v_{t+1}
 
-    To be notice, for the first step, v_{t+1} = gradient
+    To be noticed, for the first step, v_{t+1} = gradient
 
     Here : where p, v and u denote the parameters, accum, and momentum respectively.
 
@@ -89,8 +89,8 @@ class SGD(Optimizer):
         momentum (float): A floating point value the momentum. should be at least 0.0. Default: 0.0.
         dampening (float): A floating point value of dampening for momentum. should be at least 0.0. Default: 0.0.
         weight_decay (float): Weight decay (L2 penalty). It should be in range [0.0, 1.0]. Default: 0.0.
-        nesterov (bool): Enables the Nesterov momentum. If use nesterov, momentum must greater then 0,
-                         and dampening must equal to 1. Default: False.
+        nesterov (bool): Enables the Nesterov momentum. If use nesterov, momentum must be positive,
+                         and dampening must equal to 0.0. Default: False.
         loss_scale (float): A floating point value for the loss scale. Should be not less than 1.0. Default: 1.0.
 
     Inputs:
@@ -134,8 +134,8 @@ class SGD(Optimizer):
         if isinstance(momentum, float) and momentum < 0.0:
             raise ValueError("momentum should be at least 0.0, but got momentum {}".format(momentum))
 
-        if nesterov and (momentum <= 0 or dampening != 0):
-            raise ValueError("If use nesterov, momentum must be positive and dampening must equal to 0,"
+        if nesterov and (momentum <= 0.0 or dampening != 0.0):
+            raise ValueError("If use nesterov, momentum must be positive and dampening must equal to 0.0,"
                              "but got momentum {}, dampening {}".format(momentum, dampening))
 
         if isinstance(dampening, int):